# How to calculate OEE

Overall Equipment Effectiveness (OEE) is a powerful metric. Considered the gold standard for measuring manufacturing productivity, the OEE key performance indicator (KPI) brings together data on availability, performance and quality to tell you the percentage of manufacturing time that is truly productive.

## How to calculate OEE

OEE is measured as the product of three factors – availability, performance and quality. Here’s the OEE calculation in its simplest form:

OEE = Availability x Performance x Quality

Availability = run time/total time

Performance = total count of parts/target count (based on a standard)

Quality = good count/total count

Download this whitepaper to see how to implement OEE measures in your packaging hall to improve plant efficiency cost effectively and increase output.

### Let’s examine each element of the OEE formula in more detail:

Availability: This is the percentage of time the machine is ready to produce, working properly, and not in the midst of changeovers or adjustments. Availability takes into account any events that stop planned production, whether unplanned (equipment failure, material shortages, etc.) or planned (product changeovers). While it’s not possible to eliminate planned events, it’s important to include them in the calculation as they still represent time that could otherwise be used for manufacturing. In many cases – including changeovers –this time could be significantly reduced.

Availability rate = Available time (scheduled operating time − downtime) ÷ Scheduled operating time

Performance: This is the ratio of output produced compared with a standard. For standard output, use the best output rate known to be produced on the machine. This rate takes into account Performance Loss, which is anything that causes the manufacturing process to run at less than the maximum possible speed. This could be machine wear, substandard materials, jams, errors, and so on.

Performance rate = Actual output ÷ Standard output

Quality: Quality rate is the ratio of good output compared with actual output. It takes into account Quality Loss, that is parts that do not meet quality standards and require rework or scrapping.

Quality rate = Right-first-time output ÷ Actual output

## OEE formula

OEE is calculated by multiplying the three factors above to deliver a percentage.

The OEE performance calculation looks like this:

OEE (%) = Availability rate × Performance rate × Quality rate

### Example of OEE calculation

Availability

• Gross available time = 7 hours (420 minutes)
• Planned downtime = 40 minutes

Scheduled time = 420 – 40 = 380 minutes

• Breakdowns = 15 minutes
• Minor stoppages = 10 minutes
• Setup and adjustments = 15 minutes
Downtime = 40 minutes

Available time = Scheduled time – Downtime = 380 – 40 = 340 minutes

Availability rate = Available time ÷ Scheduled time = 340 ÷ 380 mins = 89%

Performance

• Standard output = 500 parts
• Actual output = 250 parts

Performance rate = Actual output ÷ Standard output = 250 ÷ 500 parts = 50%

Quality

• Actual output = 250 parts
• Defective parts, rejects, scrap = 25 parts

Good parts = 250 – 25 = 225 parts

Quality Rate = Right-first-time output ÷ Total actual output = 225 good parts ÷ 250 actual parts produced = 90%

OEE performance calculation:

OEE = 89% Availability x 50% Performance x 90% Quality = 40%

## What’s a good OEE score?

Now you’ve got an OEE score, what does it mean? Some manufacturers look to the following OEE benchmarks:

100% = Perfect production. You are manufacturing only good parts, as fast as possible, with no down time. In OEE language, that’s 100% Quality, 100% Performance and 100% Availability.

85% = This is what’s commonly recognised as world-class OEE score and a suitable long-term goal. It requires 90% Availability, 95% Performance and 99% Quality.

60% = Fairly typical for most manufacturers today. It means there is substantial room for improvement.

40% = Not uncommon for manufacturers who are just starting to measure and improve their performance. It is a low score but, in most cases, can be easily improved through specific measures, such as tracking the reasons for down time and addressing them one by one.

But OEE benchmarks can be a distraction. Avoid comparing your score with dissimilar processes and external OEE benchmarks. As Jeffrey Liker, co-author of The Toyota Way to Lean Leadership, explains in this Industry Week article, “OEE performance is relative to a baseline for a given piece of equipment; therefore it is specific to that equipment and not comparable across departments or plants.”

As a benchmark, what is considered a “good” OEE score?

At the end of the day, it’s not about the number, it’s about what you do to improve that number. You might start with an OEE score of 20%, but if you can double that score to 40%, you’re obviously making the right steps towards a productive facility.

## How to get OEE data collection right

How do you collect the right data to calculate OEE? Previously, manufacturers would rely on manual data collection, but a better and more reliable way is to automate OEE data collection using control systems, sensors and connected devices.

With so much of the production line computerised, information on quality and quantity can be captured and analysed at almost every stage of the process. It comes down to choosing the right platform.

For example, OFS Systems is an automated software program that tracks downtime and lets you see exactly how to increase asset utilisation, reduce operating cost and boost efficiency. With OFS, all OEE and downtime data is displayed in real time, so you can respond to events as they happen.

By automating OEE data collection, you can ensure the data is accurate and provided in real-time. You can also put some rationale behind the number, for example, by capturing reasons for downtimes and equipment stoppages. In this way, your OEE KPI becomes more than a number, it becomes a tool for improvement.

## How to monitor OEE

There’s no value in calculating OEE once; you need to use the metric to improve production. That’s why OEE monitoring is crucial.

Set an OEE target that will drive solid, incremental improvement. Real-time OEE monitoring should be prominently displayed throughout the plant floor. This will keep your team motivated to achieve the target as well as alert them to any issues. Use OEE KPI dashboards to make the information readily available, to the right people, in real-time.

Technology is always evolving. From April 2018, Matthews’ iDSnet Manager can be used with the OFS reporting module to deliver OEE metrics across the production line (as a result of the Matthews and OFS technology partnership). This integrated module delivers seamless OEE KPI dashboards and automatic Quality Assurance (QA) reporting with all OEE and downtime data displayed in real time. So your business is able to see actual production efficiencies, including idle times and breakdowns, plus reports on what’s causing losses.

### Here are some quick do’s and don’ts when using the OEE KPI:

DON’T use OEE primarily as a high-level KPI

DO use OEE as a measure of improvement in specific areas

DON’T multiply OEE across several production lines on the factory floor

DO use it on focused processes or machinery so you can easily identify opportunities for improvement

DON’T measure yourself against a “world-class” OEE benchmark

Here’s how to harness the power of metrics. Do you need help with OEE data collection and monitoring? Matthews Australasia can help you measure and visualise your OEE to increase operational efficiency and plant performance. Contact us today.

Check out these blogs in “lean manufacturing & OEE” for more information.

This whitepaper has a whole lot of “do’s” for best practice labelling and coding. In the face of constantly evolving packaging demands and trends, see what lessons you can learn from the experiences of Australian companies getting it right.

Looking for highly informative case studies, whitepapers and infographics for manufacturing? Or videos showing solutions in action and lots of detailed of brochures? Find all that and more in Matthews’ large resource library. It also has presentations we’ve done to industry bodies and articles from our thought leaders. Plus, its all free to download!

Image credit: iStock / flytosky11

#### Mark Dingley

Mark Dingley is Chairman of the Australian Packaging and Processing Machinery Association (APPMA) and is the CEO at Matthews Australasia. With 25 years of experience in the product identification industry and the wealth of knowledge gained from working closely with industry associations in developing and implementing standards & best practice, Mark is able to assist manufacturers with a range of issues from getting real-time visibility of their production line, improving automation, establishing quality assurance using machine vision to selecting the best fit technology for coding and labelling applications. Mark Dingley's LinkedIn Profile

#### by Mark Dingley

Mark Dingley is Chairman of the Australian Packaging and Processing Machinery Association (APPMA) and is the CEO at Matthews Australasia. With 25 years of experience in the product identification industry and the wealth of knowledge gained from working closely with industry associations in developing and implementing standards & best practice, Mark is able to assist manufacturers with a range of issues from getting real-time visibility of their production line, improving automation, establishing quality assurance using machine vision to selecting the best fit technology for coding and labelling applications. Mark Dingley's LinkedIn Profile